code: def create_attention_mask(
      input_ids: torch.Tensor, tokenizer: PreTrainedTokenizer
  ):
      """Creates an attention mask for the input_ids tensor. This also sets the last padding token ID to 1 if it
      exists.
  
      Args:
          input_ids (torch.Tensor): The input tensor.
          tokenizer (PreTrainedTokenizer): The tokenizer used to encode the input.
  
      Returns:
          torch.Tensor: The attention mask tensor.
  
      Example:
          >>> import torch # noqa
          >>> from transformers import PreTrainedTokenizer
          >>> tokenizer = PreTrainedTokenizer.from_pretrained('bert-base-uncased')
          >>> input_sentence = "This is an example sentence."
          >>> input_ids = tokenizer.encode(input_sentence, add_special_tokens=True)
          >>> attention_mask = create_attention_mask(input_ids, tokenizer)
          >>> attention_mask
          tensor([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
      """
      attention_mask = input_ids != tokenizer.pad_token_id
      # Last token may not be padding if we've already hit the max sequence length
      if not attention_mask[-1]:
          # last token is padding, always attended to even if it is padding
          attention_mask[-1] = 1
      attention_mask = attention_mask.to(torch.int64)
      return attention_mask
  
imports: import copy
  import logging
  import tempfile
  from typing import Dict, Optional, Tuple, TYPE_CHECKING, Union
  import torch
  import torch.nn.functional
  import transformers
  from bitsandbytes.nn.modules import Embedding
  from packaging import version
  from transformers import AutoConfig, AutoModelForCausalLM, PreTrainedModel, PreTrainedTokenizer, TextStreamer
  from ludwig.constants import IGNORE_INDEX_TOKEN_ID, LOGITS, PREDICTIONS, PROBABILITIES
  from ludwig.schema.trainer import LLMTrainerConfig
  from ludwig.utils.error_handling_utils import default_retry
  from ludwig.utils.logging_utils import log_once
  from ludwig.utils.model_utils import find_embedding_layer_with_path
label_desc: Use image node_id 8 for calling a global function with example usage: create_attention_mask(input_ids, tokenizer) and returns: attention_mask